Thursday, August 31, 2017

Analysis of Competing Hypothesis for Investigating Lone Wolf Terrorism

Summary and Critique by Michael Pouch

Lisa Kaati and Pontus Svenson uses Analysis of Competing Hypothesis (ACH) to help introduce a model to target similarities between different lone wolf cases. The purpose of the study is to outline this analytic tool to investigate lone wolf terrorists by showing how this method could be applied.

Before the authors began to examine their study, they introduce and define what lone wolf terrorism is. Next, they looked at the characteristics regarding the lone wolves background, and behavior that lone wolves share. They also point out the difficulty that law enforcement and intelligence community have to prevent lone wolf terrorist attacks. They specify that it is unfeasible for analysts to gather information and evaluate all data concerning radicalization processes of possible lone wolf terrorists, without any analytic method or process. However, analytic tools that assist the analysts could help facilitate the process. This will help gather and scope the information to gather more data and investigate more possibilities for lone wolf radicalization. One these tools that the authors mention was ACH.

When identifying a hypothesis for lone wolf terrorism, while using ACH, the analyst needs to pose hypotheses regarding them and their behavior. Foremost, they need to brainstorm possible hypothesis by making a list of significant evidence for and against each hypothesis. Next, the evidence needs to be evaluated by the likelihood of alternative hypotheses or helpfulness during the investigation. This will help by drawing tentative conclusions about the hypothesis and have an objective during the investigation. Lastly, the analyst proceeds to collect information about an individual with the ACH format, as shown in figure 1.

Figure 1: Two simplified examples to illustrate template hypothesis. The hypotheses are at the top and the evidence down the side. The left matrix is a hypothesis regarding the characteristics in background and behavior of lone wolf terrorists. The right matrix illustrates hypotheses regarding a terrorist attack.

The researchers describe an outline that can be used to categorize and analyze about possible lone wolf terrorists in the effort to prevent an attack while using ACH (Shown in figure 2).  First, the analyst identifies a hypothesis to begin a framework for the examination of a possible lone wolf. Second, the hypothesis is constantly developing and cultivating to help scope and specify a likely lone wolf. Third, is the process of collecting information that confirms or refute the hypotheses that
Figure 2: Mode of operation for the framework.
were started. The information can originate from a diverse number of sources such as Twitter, Facebook, web blogs, police reports, intelligence reports, tips and web forums. Fourth, is the progression of collecting relevant information and linking it to the hypotheses that it supports. After analyzing and connecting relevant information about each individual, the hypothesis is fragmented into additional explicit statements until the statements become observable actions called indicators. Lastly, when there is enough evidence, ACH warns the analyst so that appropriate action can be taken.

The use of ACH to help prevent an attack from a lone wolf is likely an effective analytic method to use to help organize and have a framework for identifying a lone wolf. However, there is room for bias in selecting the template hypothesis, relevant evidence, and weighing the individual to likely become a possible lone wolf. Due to this, there is no guarantee that ACH will automatically select a possible lone wolf attacker. Despite bias in the selecting and evaluating process, ACH does help create a systematic process that increases the odds of preventing a lone wolf attack by giving valuing and indicating  a possible lone wolf. Additionally, ACH helps the analyst leave a trail of evidence that can be interpreted. Overall, ACH is a useful analytic tool to establish a framework of potential lone wolves that can be measured.

Citation: Kaati, L., & Svenson, P. (2011). Analysis of Competing Hypothesis for Investigating Lone Wolf Terrorist. 2011 European Intelligence and Security Informatics Conference. doi:10.1109/eisic.2011.60.


  1. This comment has been removed by the author.

  2. I like your critique, specially on pointing out that "there is room for bias in selecting the template hypothesis, relevant evidence, and weighing the individual to likely become a possible lone wolf". It brings out important point of preconceived notion of the analyst toward the individual and his own cognitive bias can some time lead him to be more lenient or stricter while using this technique. Great article.

  3. Cognitive bias is driving factor that can cause an unlikely estimate or conclusion. If analysts are undertaking the demand to confirm one hypothesis they think is probably true, they can easily be led off the target by the fact that there is so much evidence to support their point of view. If the evidence seems to support the preferred hypothesis, they fail to acknowledge that most of this evidence is also reliable with other justifications or conclusions, and that these other options have not been refuted. Overall, ACH makes an effort to guard against the various cognitive biases that the analyst may have, but it is up to the analyst to offer competing reasonable alternatives and have them compete against each other for the analyst's support, rather than estimating their probability one at a time.

  4. I like how you say ACH does assist with creating a systematic process that helps increase the odds of preventing a lone wolf attack. Did Kaati or Svenson show any numbers that it can help prevent attacks?

  5. I was wondering the same thing as Jared. Is there any real statistical evidence to back up whether or not ACH actually increases the probability that the analyst is successful in forecasting for their intelligence question

  6. The authors did not have any statistical evidence to back up his claims.